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Blog on Machine, Think!

Personal blog · machinethink.net/blogaihardware

Blog on Machine, Think! is a personal blog at machinethink.net about ai and hardware. Since 2017, 15 different Hacker News readers have linked it 17 times, most often “One-shot object detection”. The last post was in 2022, but the archive is still widely read.

Visit the blog
17mentions?
15HN people?
2017–2021first – last linked?
Links on Hacker News per year · peak 8 in 2017

Most-linked posts?

  1. One-shot object detection
    3 people · 3 mentions · first linked 2018-06-09
  2. A peek inside Core ML
    2 people · 2 mentions · first linked 2017-09-03
  3. The lost art of 3D rendering without shaders
    2 people · 2 mentions · first linked 2017-01-21

What Hacker News says?

  1. You can do some refinement right now already (from WWDC 2019). But yes, most models are trained on NVIDIA GPUs that are deep learning. All of the other model types can already be trained on regular CPUs. https://machinethink.net/blog/coreml-training-part1/

    Comment linking /blog/coreml-training-part1/

    on “Apple announces it will switch to its own processors for future Macs”
  2. Submitted The lost art of 3D rendering without shaders as a story · 319 points

    HN discussion
  3. It's not misleading assuming you know the field. If you don't you might not realize they are comparing ResNet (designed for ultimate performance) vs EffcientNet to show how close it gets in accuracy in the FLOPs budget. Note that the best accuracy for EffcientNet is roughly 1-2% better than ResNet/ResNeXT/SENet/etc but does have a much better FLOPs budget. But these other architectures were never optimised for FLOPs…

    Comment linking /blog/mobile-architectures/

    on “Alphafold”
  4. Submitted Apple machine learning in 2020: What’s new? as a story · 95 points

    HN discussion
  5. Is it? The edge TPU can do MobileNet V2 at 100 FPS. An iPhone 7 can do it at 145 FPS (source https://machinethink.net/blog/mobilenet-v2/ ) The deal is though that the Edge TPU is able to do it at much lower power.

    Comment linking /blog/mobilenet-v2/

    on “Google Coral Edge TPU”
  6. Submitted Machine learning on mobile: on the device or in the cloud? as a story · 81 points

    HN discussion
  7. Submitted The lost art of 3D rendering without shaders as a story · 4 points

    HN discussion
  8. Submitted A peek inside Core ML as a story · 3 points

    HN discussion
  9. Submitted Convolutional neural networks on the iPhone with VGGNet as a story · 3 points

    HN discussion
  10. Submitted One-shot object detection as a story · 2 points

    HN discussion
  11. Submitted One-shot object detection as a story · 2 points

    HN discussion
  12. Submitted Compressing deep neural nets as a story · 2 points

    HN discussion
  13. Submitted New mobile neural network architectures benchmarked in iOS as a story · 1 points

    HN discussion
  14. Submitted One-shot object detection as a story · 1 points

    HN discussion
  15. Submitted A peek inside Core ML as a story · 1 points

    HN discussion
  16. Submitted YOLO: Core ML versus MPSNNGraph as a story · 1 points

    HN discussion
  17. Submitted YOLO: Core ML versus MPSNNGraph as a story · 1 points

    HN discussion

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